Papers to Appear in Subsequent Issues

Variable selection with Hamming loss Cristina Butucea, Natalia A. Stepanova, and Alexandre B. Tsybakov
Functional Data Analysis by Matrix Completion Marie-Hélène Descary and Victor Michael Panaretos
Computation of Maximum Likelihood Estimates in Cyclic Structural Equation Models Mathias Drton, Christopher Fox, and Y. Samuel Wang
Randomization-based causal inference from split-plot designs Anqi Zhao, Peng Ding, Rahul Mukerjee, and Tirthankar Dasgupta
A New Perspective on Robust M-Estimation: Finite Sample Theory and Applications to Dependence-Adjusted Multiple Testing Wen-Xin Zhou, Koushiki Bose, Jianqing Fan, and Han Liu
Robust Covariance and Scatter Matrix Estimation under Huber’s Contamination Model Mengjie Chen, Chao Gao, and Zhao Ren
Empirical best prediction under a nested error model with log transformation Isabel Molina and Nirian Martin
Backward Nested Descriptors Asymptotics with Inference on Stem Cell Differentiation Stephan Huckemann and Benjamin Eltzner
Change-point detection in multinomial data with a large number of categories Guanghui Wang, Changliang Zou, and Guosheng Yin
Local Asymptotic Normality Property for Fractional Gaussian Noise Under High-Frequency Observations Masaaki Fukasawa and Alexandre Brouste
Global Testing Against Sparse Alternatives under Ising Models Rajarshi Mukherjee, Sumit Mukherjee, and Ming Yuan
Principal Component Analysis for Second-order Stationary Vector Time Series Jinyuan Chang, Bin Guo, and Qiwei Yao
Estimation of a monotone density in s-sample biased sampling models Kwun Chuen Gary Chan, Hok Kan Ling, Tony Sit, and Sheung Chi Phillip Yam
Community Detection in Degree-Corrected Block Models Chao Gao, Zongming Ma, Anderson Zhang, and Harrison Zhou
CLT for Largest Eigenvalues and Unit Root Testing for High-Dimensional Nonstationary Time Series Guangming Pan, Bo Zhang, and Jiti Gao
Smooth Backfitting for Errors-in-Variables Additive Models Kyunghee Han and Byeong U Park
Unifying Markov Properties for Graphical Models Steffen Lilholt Lauritzen and Kayvan Sadeghi
Adaptation in log-concave density estimation Arlene Kyoung Hee Kim, Adityanand Guntuboyina, and Richard John Samworth
Exact recovery in the Ising blockmodel Quentin Berthet, Philippe Rigollet, and Piyush Srivastava
Weak convergence of a pseudo maximum likelihood estimator for the extremal index Betina Berghaus and Axel Bücher
Semi-parametric efficiency bounds for high-dimensional models Jana Jankova and Sara van de Geer
Limit theorems for eigenvectors of the normalized Laplacian for random graphs Minh Tang and Carey Priebe
Fréchet regression for random objects with Euclidean Predictors Alexander Petersen and Hans-Georg Müller
On the Optimality and Sub-optimality of PCA in Spiked Random Matrix Models Amelia Perry, Alexander S. Wein, Afonso S. Bandeira, and Ankur Moitra
On the Exponentially Weighted Aggregate with the Laplace Prior Arnak Dalalyan, Edwin Grappin, and Quentin Paris
Goodness-of-fit Testing of Error Distribution in Linear Measurement Error Models Hira L. Koul, Weixing Song, and Xiaoqing Zhu
Finding a Large Submatrix of a Gaussian Random Matrix David Gamarnik and Quan Li
Support Points Simon Mak and V. Roshan Joseph
Debiasing the Lasso: Optimal Sample Size for Gaussian Designs Adel Javanmard and Andrea Montanari
Margins of Discrete Bayesian Networks Robin Evans
Multi-threshold Accelerated Failure Time Model Jialiang Li and Baisuo Jin
Divide and Conquer in Non-Standard Problems and the Super-Efficiency Phenomenon Moulinath Banerjee, Cecile Durot, and Bodhisattva Sen
Rank Verification for Exponential Families Kenneth Hung and William Fithian
Measuring and testing for interval quantile independence Liping Zhu, Yaowu Zhang, and Kai Xu
Barycentric Subspace Analysis on Manifolds Xavier Pennec
The Landscape of Empirical Risk for Non-convex Losses Song Mei, Yu Bai, and Andrea Montanari
Designs with Blocks of Size Two and Applications to Microarray Experiments Janet Godolphin
Sub-Gaussian estimators of the mean of a random vector Gábor Lugosi and Shahar Mendelson
Local robust estimation of the Pickands dependence function Mikael Escobar-Bach, Yuri Goegebeur, and Armelle Guillou
Optimal rates for finite mixture estimation Jonas Kahn and Philippe Heinrich
Sub-Gaussian estimators of the mean of a random matrix with heavy-tailed entries Stanislav Minsker
Causal Inference in Partially Linear Structural Equation Models: Identifiability and Estimation Dominik Rothenhäusler, Jan Ernest, and Peter Bühlmann
On MSE-optimal crossover designs Christoph Neumann and Joachim Kunert
Testing for periodicity in functional time series Siegfried Hörmann, Piotr Kokoszka, and Gilles Nisol
Limiting Behavior of Eigenvalues in High-dimensional MANOVA via RMT Zhidong Bai, Kwok-Pui Choi, and Yasunori Fujikoshi
Two-sample Kolmogorov-Smirnov type tests revisited: Old and new tests in terms of local levels Helmut Finner and Veronika Gontscharuk
Robust Gaussian Stochastic Process Emulation Mengyang Gu, Xiaojing Wang, and Jim Berger
Convergence of contrastive divergence algorithm in exponential family Bai Jiang, Tung-Yu Wu, Yifan Jin, and Wing Hung Wong
Combinatorial Inference for Graphical Models Matey Neykov, Junwei Lu, and Han Liu
Overcoming the Limitations of Phase Transition by Higher Order Analysis of Regularization Techniques Haolei Weng, Arian Maleki, and Le Zheng
Estimation and Prediction using generalized Wendland Covariance Functions under fixed domain asymptotics Moreno Bevilacqua, Tarik Faouzi, Reinhard Furrer, and Emilio Porcu
Optimal adaptive estimation of linear functionals under sparsity Olivier Collier, Laetitia Comminges, Alexandre Tsybakov, and Nicolas Verzelen
High-dimensional consistency in score-based and hybrid structure learning Preetam Nandy, Alain Hauser, and Marloes H. Maathuis
A New Scope of Penalized Empirical Likelihood with High-Dimensional Estimating Equations Jinyuang Chang, Cheng Yong Tang, and Tong Tong Wu
Approximate ℓ0-penalized estimation of piecewise-constant signals on graphs Zhou Fan and Leying Guan
Information Measures, Experiments, Multi-category Hypothesis Tests, and Surrogate Losses John C Duchi, Khashayar Khosravi, and Feng Ruan
Halfspace depths for scatter, concentration and shape matrices Davy Paindaveine and Germain Van Bever
Multilayer tensor factorization with applications to recommender systems Xuan Bi, Annie Qu, and Xiaotong Shen
Principal Component Analysis for Functional Data on Riemannian Manifolds and Spheres Xiongtao Dai and Hans-Georg Müller
Assessing Robustness of Classi fication using Angular Breakdown Point Junlong Zhao, Guan Yu, and Yufeng Liu
Tail-greedy bottom-up data decompositions and fast multiple change-point detection Piotr Fryzlewicz
ROCKET: Robust Confidence Intervals via Kendall’s Tau for Transelliptical Graphical Models Rina Foygel Barber and Mladen Kolar
Adaptive invariant density estimation for ergodic diffusions over anisotropic classes Claudia Strauch
Chebyshev polynomials, moment matching, and optimal estimation of the unseen Yihong Wu and Pengkun Yang
Robust Low-Rank Matrix Estimation Andreas Elsener and Sara van de Geer
Sieve Bootstrap for Functional Time Series Efstathios Paparoditis
Maximuim likelihood estimation in Gaussian models under total positivity Steffen Lilholt Lauritzen, Caroline Uhler, and Piotr Zwiernik
Multiscale Scanning in Inverse Problems Katharina Proksch, Frank Werner, and Axel Munk
Slope meets Lasso: Improved oracle bounds and optimality Pierre C. Bellec, Guillaume Lecue, and Alexandre B. Tsybakov
Uniformly Valid Post-Regularization Confidence Regions for Many Functional Parameters in Z-Estimation Framework Alexandre Belloni, Victor Chernozhukov, Denis Chetverikov, and Ying Wei
Local asymptotic equivalence of pure states ensembles and quantum Gaussian white noise Cristina Butucea, Madalin Guta, and Michael Nussbaum
Extreme Quantile Treatment Effects Yichong Zhang
Optimal maximin L1-distance Latin hypercube designs based on good lattice point designs Lin Wang, Qian Xiao, and Hongquan Xu
Rho-Estimators Revisited: General Theory and Applications Yannick Baraud and Lucien Birgé
Think globally, fit locally under the Manifold Setup: Asymptotic Analysis of Locally Linear Embedding Hau-tieng Wu and Nan Wu
Nonparametric covariate-adjusted response-adaptive design based on a functional urn model Giacomo Aletti, Andrea Ghiglietti, and William F. Rosenberger
Distribution theory for hierarchical processes Federico Camerlenghi, Antonio Lijoi, Peter Orbanz, and Igor Pruenster
Restricted Strong Convexity Implies Weak Submodularity Ethan R. Elenberg, Rajiv Khanna, Alexandros G. Dimakis, and Sahand Negahban
Adaptive Estimation of the Sparsity in the Gaussian Vector Model Alexandra Carpentier and Nicolas Verzelen
Partial Least Squares Prediction in High-Dimensional Regression R. Dennis Cook and Liliana Forzani
Signal Aliasing in Gaussian Random Fields for Experiments with Qualitative Factors Ming-Chung Chang, Shao-Wei Cheng, and Ching-Shui Cheng
Approximate Optimal Designs for Multivariate Polynomial Regression Yohann De Castro, Fabrice Gamboa, Didier Henrion, Roxana Hess, and Jean-Bernard Lasserre
Efficient Estimation of Integrated Volatility Functionals via Multiscale Jackknife Jia Li, Yunxiao Liu, and Dacheng Xiu
Non-Asymptotic Rates for Manifold, Tangent Space, and Curvature Estimation Clément Levrard and Eddie Aamari
Nonparametric testing for multiple survival functions with non-inferiority margins Hsin-wen Chang and Ian W. McKeague
Estimation in the convolution structure density model. Part I: oracle inequalities Oleg Lepski and Thomas Willer
Efficient multivariate entropy estimation via k-nearest neighbour distances Thomas Benjamin Berrett, Richard John Samworth, and Ming Yuan
Posterior Graph Selection and Estimation Consistency for High-Dimensional Bayesian Dag Models Malay Ghosh, Kshitij Khare, and Xuan Cao
Locally adaptive confidence bands Tim Patschkowski and Angelika Rohde
Asymptotic Distribution-Free Change-Point Detection for Multivariate and non-Euclidean Data Lynna Chu and Hao Chen
Statistics on the (Compact) Stiefel Manifold: Theory and Applications Rudrasis Chakraborty and Baba Vemuri
Goodness-of-fit tests for the functional linear model based on randomly projected empirical processes Juan A. Cuesta-Albertos, Eduardo García-Portugués, Manuel Febrero-Bande, and Wenceslao González-Manteiga
Cross: Efficient Low-rank Tensor Completion Anru Zhang
Convolved Subsampling Estimation with Applications to Block Bootstrap Johannes Tewes, Daniel J. Nordman, and Dimitris N. Politis
Feature elimination in kernel machines in moderately high dimensions Sayan Dasgupta, Yair Goldberg, and Michael R Kosorok
Testing in High-Dimensional Spiked Models Iain M Johnstone and Alexei Onatski
Covariate balancing propensity score by tailored loss functions Qingyuan Zhao
High-dimensional covariance matrices in elliptical distributions with application to spherical test Jiang Hu, Weiming Li, Zhi Liu, and Wang Zhou
A critical threshold for design effects in network sampling Karl Rohe
The geometry of hypothesis testing over convex cones: Generalized likelihood ratio tests and minimax radii Yuting Wei
Permutation p-value approximation via generalized Stolarsky invariance Art B Owen
Nonparametric Implied Levy Densities Likuan Qin and Viktor Todorov
Canonical correlation coefficients of high-dimensional Gaussian vectors: finite rank case Zhigang Bao, Jiang Hu, Guangming Pan, and Wang Zhou
Uniform Projection Designs Fasheng Sun, Yaping Wang, and Hongquan Xu
On model selection from a finite family of possibly misspecified time series models Hsiang-Ling Hsu, Ching-Kang Ing, and Howell Tong
Estimating the Algorithmic Variance of Randomized Ensembles via the Bootstrap Miles Lopes
Efficient Nonparametric Bayesian Inference for X-ray transforms Francois Monard, Richard Nickl, and Gabriel P Paternain
Generalized Random Forests Susan Athey, Julie Tibshirani, and Stefan Wager
Approximating faces of marginal polytopes in discrete hierarchical models Nanwei Wang, Johannes Rauh, and Helene Massam
CHIME: Clustering of High-Dimensional Gaussian Mixtures with EM Algorithm and Its Optimality Tony Cai, Jing Ma, and Linjun Zhang
Bayesian fractional posteriors Anirban Bhattacharya, Debdeep Pati, and Yun Yang
Distributed Estimation of Principal Eigenspaces Jianqing Fan, Dong Wang, Kaizheng Wang, and Ziwei Zhu
Exponential ergodicity of the Bouncy Particle Sampler George Deligiannidis, Alexandre Bouchard-Cote, and Arnaud Doucet
The Zig-Zag process and Super-Efficient Sampling for Bayesian Analysis of Big Data Joris Bierkens, Paul Fearnhead, and Gareth O. Roberts
Estimation of Large Covariance and Precision Matrices from Temporally Dependent Observations Hai Shu and Bin Nan
Bootstrap tuning in ordered model selection Vladimir Spokoiny and Niklas Willrich
Sequential change-point detection based on nearest neighbors Hao Chen
Prediction when fitting simple models to high-dimensional data Lukas Steinberger and Hannes Leeb
Two-Sample and ANOVA Tests for High Dimensional Means Song X Chen, Jun Li, and Pingshou Zhong
Valid confidence intervals for post-model-selection predictors François Bachoc, Hannes Leeb, and Benedikt Poetscher
A robust and efficient approach to causal inference based on sparse sufficient dimension reduction Shujie Ma, Liping Zhu, Zhiwei Zhang, Chih-Ling Tsai, and Raymond Carroll
A Classification Criterion for Definitive Screening Designs Eric Schoen, Pieter Eendebak, and Peter Goos
The Maximum Likelihood Threshold of a Path Diagram Mathias Drton, Christopher Fox, Andreas Käufl, and Guillaume Pouliot
Convex Regularization for High-dimensional Multi-response Tensor Regression Garvesh Raskutti, Ming Yuan, and Han Chen
Maximum likelihood estimation in transformed linear regression with non-normal errors Xingwei Tong, Fuqing Gao, Kani Chen, Dingjiao Cai, and Jianguo Sun
Large Sample Theory for Merged Data from Multiple Sources Takumi Saegusa
Khinchine’s theorem and Edgeworth approximations for weighted sums Sergey G. Bobkov
Hypothesis Testing for Densities and High-Dimensional Multinomials: Sharp Local Minimax Rates Sivaraman Balakrishnan and Larry Wasserman
Distributed Inference for Quantile Regression Processes Stanislav Volgushev, Shih-Kang Chao, and Guang Cheng
Gaussian approximation of maxima of Wiener functionals and its application to high-frequency data Yuta Koike
Causal Dantzig: fast inference in linear structural equation models with hidden variables under additive interventions Dominik Rothenhäusler, Peter Bühlmann, and Nicolai Meinshausen
Non-penalized variable selection in high-dimensional linear model settings via generalized fiducial inference Jonathan Paul Williams and Jan Hannig
The BLUE in regression models with correlated errors Holger Dette, Andrey Pepelyshev, and Anatoly Zhigljavsky
Adaptive-to-model checking for regressions with diverging number of predictors Falong Tan and Lixing Zhu
Super-resolution estimation of cyclic arrival rates Ningyuan Chen, Donald K.K. Lee, and Sahand N. Negahban
Sequential Multiple Testing with Generalized Error Control: An Asymptotic Optimality Theory Yanglei Song and Georgios Fellouris
Nonparametric Screening under Conditional Strictly Convex Loss for Ultrahigh Dimensional Sparse Data Xu Han
Local stationarity and time-inhomogeneous Markov chains Lionel Truquet
High-dimensional change-point detection with sparse alternatives Farida Enikeeva and Zaid Harchaoui
Perturbation Bootstrap in Adaptive Lasso Debraj Das, Karl Gregory, and Soumendra Nath Lahiri
Estimation bounds and sharp oracle inequalities of regularized procedures with Lipschitz loss functions Guillaume Lecue, Pierre Alquier, and Vincent Cottet
Cross validation for locally stationary processes Stefan Richter and Rainer Dahlhaus
Generalized Cluster Trees and Singular Measures Yen-Chi Chen
Spectral Method and Regularized MLE are Both Optimal for Top-K Ranking Yuxin Chen, Jianqing Fan, Cong Ma, and Kaizheng Wang
Negative association, ordering and convergence of resampling methods Mathieu Gerber, Nicolas Chopin, and Nick Whiteley
On deep learning as a remedy for the curse of dimensionality in nonparametric regression Benedikt Bauer and Michael Kohler
Convergence rates of least squares regression estimators with heavy tailed errors Qiyang Han and Jon A. Wellner
Convergence complexity analysis of Albert and Chib’s algorithm for Bayesian probit regression Qian Qin and James P. Hobert
On Testing Conditional Qualitative Treatment Effects Chengchun Shi, Wenbin Lu, and Rui Song
Dynamic network models and graphon estimation Marianna Pensky
The two-to-infinity norm and singular subspace geometry with applications to high-dimensional statistics Joshua Cape, Minh Tang, and Carey E. Priebe
Isotonic regression in general dimensions Qiyang Han, Tengyao Wang, Sabyasachi Chatterjee, and Richard John Samworth
Property Testing in High Dimensional Ising Models Matey Neykov and Han Liu
A knockoff filter for high-dimensional selective inference Rina Foygel Barber and Emmanuel J Candes
Semi-supervised Inference: General Theory and Estimation of Means Anru Zhang, Lawrence D. Brown, and T. Tony Cai
Penalized Estimation in Additive Regression with High-Dimensional Data Zhiqiang Tan and Cun-Hui Zhang